Overview

Dataset statistics

Number of variables44
Number of observations20336
Missing cells222441
Missing cells (%)24.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.8 MiB
Average record size in memory352.0 B

Variable types

Numeric38
Unsupported1
Categorical5

Alerts

SBP is highly correlated with MAPHigh correlation
MAP is highly correlated with SBP and 1 other fieldsHigh correlation
DBP is highly correlated with MAPHigh correlation
BaseExcess is highly correlated with HCO3 and 1 other fieldsHigh correlation
HCO3 is highly correlated with BaseExcess and 1 other fieldsHigh correlation
pH is highly correlated with BaseExcessHigh correlation
PaCO2 is highly correlated with HCO3High correlation
BUN is highly correlated with CreatinineHigh correlation
Creatinine is highly correlated with BUNHigh correlation
Bilirubin_direct is highly correlated with Bilirubin_totalHigh correlation
Bilirubin_total is highly correlated with Bilirubin_directHigh correlation
Hct is highly correlated with HgbHigh correlation
Hgb is highly correlated with HctHigh correlation
Unit1 is highly correlated with Unit2High correlation
Unit2 is highly correlated with Unit1High correlation
ICULOS is highly correlated with HoursHigh correlation
SepsisLabel is highly correlated with SepsisHigh correlation
Sepsis is highly correlated with SepsisLabelHigh correlation
Hours is highly correlated with ICULOSHigh correlation
SBP is highly correlated with MAPHigh correlation
MAP is highly correlated with SBP and 1 other fieldsHigh correlation
DBP is highly correlated with MAPHigh correlation
BaseExcess is highly correlated with HCO3 and 1 other fieldsHigh correlation
HCO3 is highly correlated with BaseExcess and 1 other fieldsHigh correlation
pH is highly correlated with BaseExcessHigh correlation
PaCO2 is highly correlated with HCO3High correlation
BUN is highly correlated with Creatinine and 1 other fieldsHigh correlation
Creatinine is highly correlated with BUN and 1 other fieldsHigh correlation
Bilirubin_direct is highly correlated with Bilirubin_totalHigh correlation
Phosphate is highly correlated with BUN and 1 other fieldsHigh correlation
Bilirubin_total is highly correlated with Bilirubin_directHigh correlation
Hct is highly correlated with HgbHigh correlation
Hgb is highly correlated with HctHigh correlation
Unit1 is highly correlated with Unit2High correlation
Unit2 is highly correlated with Unit1High correlation
ICULOS is highly correlated with HoursHigh correlation
SepsisLabel is highly correlated with SepsisHigh correlation
Sepsis is highly correlated with SepsisLabelHigh correlation
Hours is highly correlated with ICULOSHigh correlation
SBP is highly correlated with MAPHigh correlation
MAP is highly correlated with SBP and 1 other fieldsHigh correlation
DBP is highly correlated with MAPHigh correlation
BaseExcess is highly correlated with HCO3High correlation
HCO3 is highly correlated with BaseExcessHigh correlation
BUN is highly correlated with CreatinineHigh correlation
Creatinine is highly correlated with BUNHigh correlation
Bilirubin_direct is highly correlated with Bilirubin_totalHigh correlation
Bilirubin_total is highly correlated with Bilirubin_directHigh correlation
Hct is highly correlated with HgbHigh correlation
Hgb is highly correlated with HctHigh correlation
Unit1 is highly correlated with Unit2High correlation
Unit2 is highly correlated with Unit1High correlation
ICULOS is highly correlated with HoursHigh correlation
SepsisLabel is highly correlated with SepsisHigh correlation
Sepsis is highly correlated with SepsisLabelHigh correlation
Hours is highly correlated with ICULOSHigh correlation
Unit2 is highly correlated with Unit1High correlation
SepsisLabel is highly correlated with SepsisHigh correlation
Sepsis is highly correlated with SepsisLabelHigh correlation
Unit1 is highly correlated with Unit2High correlation
Temp has 235 (1.2%) missing values Missing
SBP has 258 (1.3%) missing values Missing
DBP has 7384 (36.3%) missing values Missing
EtCO2 has 20336 (100.0%) missing values Missing
BaseExcess has 7684 (37.8%) missing values Missing
HCO3 has 535 (2.6%) missing values Missing
FiO2 has 8349 (41.1%) missing values Missing
pH has 7155 (35.2%) missing values Missing
PaCO2 has 7759 (38.2%) missing values Missing
SaO2 has 12373 (60.8%) missing values Missing
AST has 14443 (71.0%) missing values Missing
BUN has 427 (2.1%) missing values Missing
Alkalinephos has 14633 (72.0%) missing values Missing
Calcium has 3789 (18.6%) missing values Missing
Chloride has 542 (2.7%) missing values Missing
Creatinine has 461 (2.3%) missing values Missing
Bilirubin_direct has 19750 (97.1%) missing values Missing
Glucose has 407 (2.0%) missing values Missing
Lactate has 12603 (62.0%) missing values Missing
Magnesium has 1388 (6.8%) missing values Missing
Phosphate has 3650 (17.9%) missing values Missing
Potassium has 433 (2.1%) missing values Missing
Bilirubin_total has 14566 (71.6%) missing values Missing
TroponinI has 19847 (97.6%) missing values Missing
Hct has 364 (1.8%) missing values Missing
Hgb has 507 (2.5%) missing values Missing
PTT has 4496 (22.1%) missing values Missing
WBC has 625 (3.1%) missing values Missing
Fibrinogen has 17769 (87.4%) missing values Missing
Platelets has 585 (2.9%) missing values Missing
Unit1 has 9522 (46.8%) missing values Missing
Unit2 has 9522 (46.8%) missing values Missing
PatientID has unique values Unique
EtCO2 is an unsupported type, check if it needs cleaning or further analysis Unsupported
BaseExcess has 2996 (14.7%) zeros Zeros

Reproduction

Analysis started2021-11-29 10:21:47.999856
Analysis finished2021-11-29 10:21:57.646149
Duration9.65 seconds
Software versionpandas-profiling v3.1.1
Download configurationconfig.json

Variables

PatientID
Real number (ℝ≥0)

UNIQUE

Distinct20336
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10173.60651
Minimum1
Maximum20643
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:21:57.694461image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1017.75
Q15084.75
median10168.5
Q315252.25
95-th percentile19320.25
Maximum20643
Range20642
Interquartile range (IQR)10167.5

Descriptive statistics

Standard deviation5879.461518
Coefficient of variation (CV)0.5779132024
Kurtosis-1.192915145
Mean10173.60651
Median Absolute Deviation (MAD)5084
Skewness0.005160825078
Sum206890462
Variance34568067.75
MonotonicityStrictly increasing
2021-11-29T11:21:57.792925image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11
 
< 0.1%
135561
 
< 0.1%
135631
 
< 0.1%
135621
 
< 0.1%
135611
 
< 0.1%
135601
 
< 0.1%
135591
 
< 0.1%
135581
 
< 0.1%
135571
 
< 0.1%
135551
 
< 0.1%
Other values (20326)20326
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
21
< 0.1%
31
< 0.1%
41
< 0.1%
51
< 0.1%
61
< 0.1%
71
< 0.1%
81
< 0.1%
91
< 0.1%
101
< 0.1%
ValueCountFrequency (%)
206431
< 0.1%
206421
< 0.1%
206411
< 0.1%
206401
< 0.1%
206391
< 0.1%
206381
< 0.1%
206371
< 0.1%
206361
< 0.1%
206351
< 0.1%
206341
< 0.1%

HR
Real number (ℝ≥0)

Distinct353
Distinct (%)1.7%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean84.06217113
Minimum30
Maximum151
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:21:57.893115image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile61
Q174
median83.5
Q393
95-th percentile109
Maximum151
Range121
Interquartile range (IQR)19

Descriptive statistics

Standard deviation14.66009796
Coefficient of variation (CV)0.1743958996
Kurtosis0.2189910597
Mean84.06217113
Median Absolute Deviation (MAD)9.5
Skewness0.3030333462
Sum1709404.25
Variance214.9184721
MonotonicityNot monotonic
2021-11-29T11:21:57.995309image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
80700
 
3.4%
90476
 
2.3%
88475
 
2.3%
84444
 
2.2%
82430
 
2.1%
85412
 
2.0%
79411
 
2.0%
70404
 
2.0%
77398
 
2.0%
87394
 
1.9%
Other values (343)15791
77.7%
ValueCountFrequency (%)
302
 
< 0.1%
331
 
< 0.1%
341
 
< 0.1%
361
 
< 0.1%
38.51
 
< 0.1%
391
 
< 0.1%
402
 
< 0.1%
41.51
 
< 0.1%
423
< 0.1%
435
< 0.1%
ValueCountFrequency (%)
1512
< 0.1%
1492
< 0.1%
1472
< 0.1%
1441
 
< 0.1%
142.751
 
< 0.1%
142.53
< 0.1%
1422
< 0.1%
141.52
< 0.1%
1402
< 0.1%
139.51
 
< 0.1%

O2Sat
Real number (ℝ≥0)

Distinct86
Distinct (%)0.4%
Missing12
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean97.47929787
Minimum27
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:21:58.097016image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum27
5-th percentile94
Q196
median98
Q399
95-th percentile100
Maximum100
Range73
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.316854526
Coefficient of variation (CV)0.0237676571
Kurtosis126.0227646
Mean97.47929787
Median Absolute Deviation (MAD)1
Skewness-6.629905027
Sum1981169.25
Variance5.367814894
MonotonicityNot monotonic
2021-11-29T11:21:58.194705image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
983484
17.1%
973382
16.6%
1003198
15.7%
992968
14.6%
962590
12.7%
951307
 
6.4%
94548
 
2.7%
97.5438
 
2.2%
98.5370
 
1.8%
96.5340
 
1.7%
Other values (76)1699
8.4%
ValueCountFrequency (%)
271
< 0.1%
34.251
< 0.1%
491
< 0.1%
51.751
< 0.1%
55.51
< 0.1%
57.51
< 0.1%
581
< 0.1%
631
< 0.1%
64.251
< 0.1%
652
< 0.1%
ValueCountFrequency (%)
1003198
15.7%
99.7567
 
0.3%
99.5250
 
1.2%
99.2568
 
0.3%
992968
14.6%
98.7574
 
0.4%
98.5370
 
1.8%
98.2572
 
0.4%
983484
17.1%
97.7572
 
0.4%

Temp
Real number (ℝ≥0)

MISSING

Distinct547
Distinct (%)2.7%
Missing235
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean36.94550992
Minimum30.5
Maximum40.03
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:21:58.300125image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum30.5
5-th percentile36.06
Q136.56
median36.94
Q337.33
95-th percentile37.89
Maximum40.03
Range9.53
Interquartile range (IQR)0.77

Descriptive statistics

Standard deviation0.5880792486
Coefficient of variation (CV)0.01591747549
Kurtosis2.959195879
Mean36.94550992
Median Absolute Deviation (MAD)0.38
Skewness-0.3045890144
Sum742641.695
Variance0.3458372027
MonotonicityNot monotonic
2021-11-29T11:21:58.397473image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37805
 
4.0%
36.89662
 
3.3%
36.67657
 
3.2%
36.78460
 
2.3%
36.56442
 
2.2%
37.5430
 
2.1%
36.5397
 
2.0%
36.72390
 
1.9%
37.17386
 
1.9%
37.11368
 
1.8%
Other values (537)15104
74.3%
ValueCountFrequency (%)
30.51
< 0.1%
31.671
< 0.1%
32.351
< 0.1%
32.521
< 0.1%
32.641
< 0.1%
32.91
< 0.1%
331
< 0.1%
33.111
< 0.1%
33.151
< 0.1%
33.251
< 0.1%
ValueCountFrequency (%)
40.031
< 0.1%
39.71
< 0.1%
39.611
< 0.1%
39.51
< 0.1%
39.351
< 0.1%
39.332
< 0.1%
39.31
< 0.1%
39.281
< 0.1%
39.221
< 0.1%
39.151
< 0.1%

SBP
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct497
Distinct (%)2.5%
Missing258
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean119.8992283
Minimum35
Maximum216
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:21:58.496096image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum35
5-th percentile96.5
Q1107.75
median117.5
Q3130
95-th percentile151
Maximum216
Range181
Interquartile range (IQR)22.25

Descriptive statistics

Standard deviation17.09910417
Coefficient of variation (CV)0.1426122955
Kurtosis0.5591623812
Mean119.8992283
Median Absolute Deviation (MAD)11
Skewness0.5726205633
Sum2407336.705
Variance292.3793633
MonotonicityNot monotonic
2021-11-29T11:21:58.596080image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
110365
 
1.8%
109359
 
1.8%
112357
 
1.8%
111355
 
1.7%
115352
 
1.7%
117343
 
1.7%
116343
 
1.7%
114340
 
1.7%
113334
 
1.6%
119327
 
1.6%
Other values (487)16603
81.6%
ValueCountFrequency (%)
351
< 0.1%
361
< 0.1%
451
< 0.1%
551
< 0.1%
562
< 0.1%
56.51
< 0.1%
571
< 0.1%
58.51
< 0.1%
611
< 0.1%
62.51
< 0.1%
ValueCountFrequency (%)
2161
 
< 0.1%
2061
 
< 0.1%
199.51
 
< 0.1%
1921
 
< 0.1%
191.51
 
< 0.1%
1911
 
< 0.1%
1902
< 0.1%
1872
< 0.1%
1861
 
< 0.1%
1854
< 0.1%

MAP
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct854
Distinct (%)4.2%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean77.93093882
Minimum22
Maximum142
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:21:58.784939image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile62.5
Q170
median76.25
Q384.5
95-th percentile98
Maximum142
Range120
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation11.1309419
Coefficient of variation (CV)0.1428308457
Kurtosis0.934054842
Mean77.93093882
Median Absolute Deviation (MAD)6.92
Skewness0.677033949
Sum1584647.71
Variance123.8978676
MonotonicityNot monotonic
2021-11-29T11:21:58.883146image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
72534
 
2.6%
73495
 
2.4%
71494
 
2.4%
74491
 
2.4%
76483
 
2.4%
75480
 
2.4%
70465
 
2.3%
69443
 
2.2%
77416
 
2.0%
68411
 
2.0%
Other values (844)15622
76.8%
ValueCountFrequency (%)
221
 
< 0.1%
27.251
 
< 0.1%
301
 
< 0.1%
34.51
 
< 0.1%
35.831
 
< 0.1%
411
 
< 0.1%
422
< 0.1%
43.251
 
< 0.1%
43.421
 
< 0.1%
443
< 0.1%
ValueCountFrequency (%)
1421
< 0.1%
1391
< 0.1%
1341
< 0.1%
133.51
< 0.1%
1331
< 0.1%
131.0851
< 0.1%
1301
< 0.1%
128.671
< 0.1%
128.51
< 0.1%
1281
< 0.1%

DBP
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct279
Distinct (%)2.2%
Missing7384
Missing (%)36.3%
Infinite0
Infinite (%)0.0%
Mean59.51185145
Minimum22
Maximum134
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:21:58.984798image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile45
Q153
median58
Q365
95-th percentile78
Maximum134
Range112
Interquartile range (IQR)12

Descriptive statistics

Standard deviation10.02244819
Coefficient of variation (CV)0.1684109626
Kurtosis1.393943938
Mean59.51185145
Median Absolute Deviation (MAD)6
Skewness0.7247974181
Sum770797.5
Variance100.4494677
MonotonicityNot monotonic
2021-11-29T11:21:59.083058image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
55460
 
2.3%
57454
 
2.2%
56422
 
2.1%
53421
 
2.1%
58398
 
2.0%
59396
 
1.9%
54387
 
1.9%
52379
 
1.9%
60377
 
1.9%
62359
 
1.8%
Other values (269)8899
43.8%
(Missing)7384
36.3%
ValueCountFrequency (%)
221
 
< 0.1%
261
 
< 0.1%
27.51
 
< 0.1%
281
 
< 0.1%
295
< 0.1%
301
 
< 0.1%
311
 
< 0.1%
31.51
 
< 0.1%
31.751
 
< 0.1%
322
 
< 0.1%
ValueCountFrequency (%)
1341
< 0.1%
1311
< 0.1%
1121
< 0.1%
110.751
< 0.1%
1101
< 0.1%
109.51
< 0.1%
108.51
< 0.1%
1082
< 0.1%
1071
< 0.1%
1051
< 0.1%

Resp
Real number (ℝ≥0)

Distinct156
Distinct (%)0.8%
Missing28
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean18.3511333
Minimum6
Maximum42
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:21:59.184246image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile13
Q116
median18
Q320.5
95-th percentile25
Maximum42
Range36
Interquartile range (IQR)4.5

Descriptive statistics

Standard deviation3.862887796
Coefficient of variation (CV)0.2104985961
Kurtosis1.457467162
Mean18.3511333
Median Absolute Deviation (MAD)2
Skewness0.8452002569
Sum372674.815
Variance14.92190212
MonotonicityNot monotonic
2021-11-29T11:21:59.280293image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
162060
 
10.1%
182007
 
9.9%
171741
 
8.6%
201562
 
7.7%
191385
 
6.8%
151272
 
6.3%
141206
 
5.9%
21991
 
4.9%
22875
 
4.3%
23572
 
2.8%
Other values (146)6637
32.6%
ValueCountFrequency (%)
61
 
< 0.1%
88
 
< 0.1%
8.251
 
< 0.1%
98
 
< 0.1%
9.54
 
< 0.1%
1071
0.3%
10.1251
 
< 0.1%
10.251
 
< 0.1%
10.512
 
0.1%
10.6251
 
< 0.1%
ValueCountFrequency (%)
421
 
< 0.1%
41.51
 
< 0.1%
402
< 0.1%
38.52
< 0.1%
381
 
< 0.1%
37.51
 
< 0.1%
374
< 0.1%
36.751
 
< 0.1%
36.52
< 0.1%
36.252
< 0.1%

EtCO2
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing20336
Missing (%)100.0%
Memory size159.0 KiB

BaseExcess
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
ZEROS

Distinct125
Distinct (%)1.0%
Missing7684
Missing (%)37.8%
Infinite0
Infinite (%)0.0%
Mean-0.3486998103
Minimum-25.5
Maximum25
Zeros2996
Zeros (%)14.7%
Negative5559
Negative (%)27.3%
Memory size159.0 KiB
2021-11-29T11:21:59.380407image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-25.5
5-th percentile-6
Q1-2
median0
Q31
95-th percentile6
Maximum25
Range50.5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.845161744
Coefficient of variation (CV)-11.02714034
Kurtosis5.010842562
Mean-0.3486998103
Median Absolute Deviation (MAD)2
Skewness-0.08744974129
Sum-4411.75
Variance14.78526884
MonotonicityNot monotonic
2021-11-29T11:21:59.478158image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
02996
 
14.7%
-11165
 
5.7%
-2913
 
4.5%
1875
 
4.3%
-3715
 
3.5%
2665
 
3.3%
3480
 
2.4%
-4476
 
2.3%
-0.5353
 
1.7%
4344
 
1.7%
Other values (115)3670
18.0%
(Missing)7684
37.8%
ValueCountFrequency (%)
-25.51
 
< 0.1%
-251
 
< 0.1%
-24.51
 
< 0.1%
-242
 
< 0.1%
-231
 
< 0.1%
-22.251
 
< 0.1%
-21.51
 
< 0.1%
-212
 
< 0.1%
-20.51
 
< 0.1%
-205
< 0.1%
ValueCountFrequency (%)
251
 
< 0.1%
241
 
< 0.1%
213
 
< 0.1%
201
 
< 0.1%
195
< 0.1%
189
< 0.1%
17.51
 
< 0.1%
175
< 0.1%
16.51
 
< 0.1%
1611
0.1%

HCO3
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct101
Distinct (%)0.5%
Missing535
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean24.40773193
Minimum5
Maximum55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:21:59.574045image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile18
Q122
median24
Q326.5
95-th percentile31
Maximum55
Range50
Interquartile range (IQR)4.5

Descriptive statistics

Standard deviation3.936552844
Coefficient of variation (CV)0.1612830252
Kurtosis3.050904352
Mean24.40773193
Median Absolute Deviation (MAD)2
Skewness0.3942297783
Sum483297.5
Variance15.4964483
MonotonicityNot monotonic
2021-11-29T11:21:59.670617image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
252056
 
10.1%
241972
 
9.7%
231783
 
8.8%
261670
 
8.2%
221407
 
6.9%
271248
 
6.1%
21921
 
4.5%
28833
 
4.1%
20684
 
3.4%
24.5589
 
2.9%
Other values (91)6638
32.6%
ValueCountFrequency (%)
51
 
< 0.1%
61
 
< 0.1%
6.52
 
< 0.1%
73
 
< 0.1%
87
< 0.1%
8.52
 
< 0.1%
98
< 0.1%
9.52
 
< 0.1%
108
< 0.1%
10.52
 
< 0.1%
ValueCountFrequency (%)
551
 
< 0.1%
511
 
< 0.1%
501
 
< 0.1%
491
 
< 0.1%
481
 
< 0.1%
47.51
 
< 0.1%
471
 
< 0.1%
46.51
 
< 0.1%
463
< 0.1%
45.51
 
< 0.1%

FiO2
Real number (ℝ≥0)

MISSING

Distinct102
Distinct (%)0.9%
Missing8349
Missing (%)41.1%
Infinite0
Infinite (%)0.0%
Mean0.509014766
Minimum0
Maximum10
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:21:59.769828image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.35
Q10.4
median0.5
Q30.5
95-th percentile0.9
Maximum10
Range10
Interquartile range (IQR)0.1

Descriptive statistics

Standard deviation0.1741220653
Coefficient of variation (CV)0.3420766486
Kurtosis737.4129205
Mean0.509014766
Median Absolute Deviation (MAD)0.1
Skewness14.6051189
Sum6101.56
Variance0.03031849361
MonotonicityNot monotonic
2021-11-29T11:21:59.867304image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.54390
21.6%
0.43627
17.8%
0.6811
 
4.0%
1506
 
2.5%
0.7483
 
2.4%
0.45419
 
2.1%
0.35313
 
1.5%
0.55260
 
1.3%
0.3165
 
0.8%
0.8135
 
0.7%
Other values (92)878
 
4.3%
(Missing)8349
41.1%
ValueCountFrequency (%)
02
 
< 0.1%
0.022
 
< 0.1%
0.034
 
< 0.1%
0.047
 
< 0.1%
0.052
 
< 0.1%
0.081
 
< 0.1%
0.111
 
< 0.1%
0.151
 
< 0.1%
0.230
0.1%
0.2052
 
< 0.1%
ValueCountFrequency (%)
101
 
< 0.1%
1506
2.5%
0.9951
 
< 0.1%
0.995
 
< 0.1%
0.984
 
< 0.1%
0.9753
 
< 0.1%
0.972
 
< 0.1%
0.9652
 
< 0.1%
0.961
 
< 0.1%
0.9551
 
< 0.1%

pH
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct153
Distinct (%)1.2%
Missing7155
Missing (%)35.2%
Infinite0
Infinite (%)0.0%
Mean7.384674911
Minimum6.63
Maximum7.73
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:21:59.966593image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum6.63
5-th percentile7.29
Q17.355
median7.39
Q37.42
95-th percentile7.47
Maximum7.73
Range1.1
Interquartile range (IQR)0.065

Descriptive statistics

Standard deviation0.05959166947
Coefficient of variation (CV)0.008069640193
Kurtosis8.812019318
Mean7.384674911
Median Absolute Deviation (MAD)0.03
Skewness-1.340091006
Sum97337.4
Variance0.003551167071
MonotonicityNot monotonic
2021-11-29T11:22:00.063320image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.4906
 
4.5%
7.38834
 
4.1%
7.37799
 
3.9%
7.39730
 
3.6%
7.41717
 
3.5%
7.42681
 
3.3%
7.35605
 
3.0%
7.36600
 
3.0%
7.43551
 
2.7%
7.34465
 
2.3%
Other values (143)6293
30.9%
(Missing)7155
35.2%
ValueCountFrequency (%)
6.631
< 0.1%
6.651
< 0.1%
6.871
< 0.1%
6.91
< 0.1%
6.921
< 0.1%
6.941
< 0.1%
6.941
< 0.1%
6.962
< 0.1%
6.971
< 0.1%
6.9751
< 0.1%
ValueCountFrequency (%)
7.731
< 0.1%
7.6951
< 0.1%
7.661
< 0.1%
7.631
< 0.1%
7.592
< 0.1%
7.5851
< 0.1%
7.581
< 0.1%
7.5751
< 0.1%
7.5651
< 0.1%
7.561
< 0.1%

PaCO2
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct188
Distinct (%)1.5%
Missing7759
Missing (%)38.2%
Infinite0
Infinite (%)0.0%
Mean40.97686253
Minimum10
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:00.238382image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile31
Q137
median40
Q344
95-th percentile53
Maximum99
Range89
Interquartile range (IQR)7

Descriptive statistics

Standard deviation7.724370697
Coefficient of variation (CV)0.1885056644
Kurtosis7.101296055
Mean40.97686253
Median Absolute Deviation (MAD)4
Skewness1.691919114
Sum515366
Variance59.66590267
MonotonicityNot monotonic
2021-11-29T11:22:00.333741image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40733
 
3.6%
39680
 
3.3%
41669
 
3.3%
38665
 
3.3%
42627
 
3.1%
37594
 
2.9%
43564
 
2.8%
36535
 
2.6%
44502
 
2.5%
35411
 
2.0%
Other values (178)6597
32.4%
(Missing)7759
38.2%
ValueCountFrequency (%)
101
 
< 0.1%
15.51
 
< 0.1%
163
 
< 0.1%
182
 
< 0.1%
18.51
 
< 0.1%
194
< 0.1%
19.51
 
< 0.1%
206
< 0.1%
20.54
< 0.1%
219
< 0.1%
ValueCountFrequency (%)
991
 
< 0.1%
981
 
< 0.1%
96.51
 
< 0.1%
941
 
< 0.1%
93.51
 
< 0.1%
932
 
< 0.1%
921
 
< 0.1%
911
 
< 0.1%
89.51
 
< 0.1%
895
< 0.1%

SaO2
Real number (ℝ≥0)

MISSING

Distinct158
Distinct (%)2.0%
Missing12373
Missing (%)60.8%
Infinite0
Infinite (%)0.0%
Mean92.95674997
Minimum29.5
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:00.432698image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum29.5
5-th percentile69
Q194.5
median97
Q398
95-th percentile99
Maximum100
Range70.5
Interquartile range (IQR)3.5

Descriptive statistics

Standard deviation9.561328494
Coefficient of variation (CV)0.1028578183
Kurtosis5.396745734
Mean92.95674997
Median Absolute Deviation (MAD)1
Skewness-2.381941831
Sum740214.6
Variance91.41900257
MonotonicityNot monotonic
2021-11-29T11:22:00.529460image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
982084
 
10.2%
971364
 
6.7%
96701
 
3.4%
99459
 
2.3%
97.5344
 
1.7%
95339
 
1.7%
96.5229
 
1.1%
94205
 
1.0%
98.5198
 
1.0%
95.5109
 
0.5%
Other values (148)1931
 
9.5%
(Missing)12373
60.8%
ValueCountFrequency (%)
29.51
< 0.1%
301
< 0.1%
311
< 0.1%
31.51
< 0.1%
401
< 0.1%
40.51
< 0.1%
41.51
< 0.1%
422
< 0.1%
431
< 0.1%
442
< 0.1%
ValueCountFrequency (%)
10021
 
0.1%
99.53
 
< 0.1%
99459
 
2.3%
98.91
 
< 0.1%
98.753
 
< 0.1%
98.5198
 
1.0%
98.2510
 
< 0.1%
982084
10.2%
97.8752
 
< 0.1%
97.755
 
< 0.1%

AST
Real number (ℝ≥0)

MISSING

Distinct949
Distinct (%)16.1%
Missing14443
Missing (%)71.0%
Infinite0
Infinite (%)0.0%
Mean182.4755218
Minimum3
Maximum9210
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:00.632519image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile14
Q123
median42
Q398
95-th percentile659.6
Maximum9210
Range9207
Interquartile range (IQR)75

Descriptive statistics

Standard deviation618.8133575
Coefficient of variation (CV)3.391212977
Kurtosis76.78142027
Mean182.4755218
Median Absolute Deviation (MAD)23
Skewness8.007395477
Sum1075328.25
Variance382929.9714
MonotonicityNot monotonic
2021-11-29T11:22:00.728618image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24131
 
0.6%
18131
 
0.6%
19123
 
0.6%
17122
 
0.6%
16118
 
0.6%
22116
 
0.6%
20111
 
0.5%
21108
 
0.5%
15106
 
0.5%
23101
 
0.5%
Other values (939)4726
 
23.2%
(Missing)14443
71.0%
ValueCountFrequency (%)
32
 
< 0.1%
41
 
< 0.1%
51
 
< 0.1%
65
 
< 0.1%
75
 
< 0.1%
811
0.1%
8.251
 
< 0.1%
8.53
 
< 0.1%
916
0.1%
9.51
 
< 0.1%
ValueCountFrequency (%)
92101
< 0.1%
85911
< 0.1%
84721
< 0.1%
77511
< 0.1%
76991
< 0.1%
76341
< 0.1%
75051
< 0.1%
7438.51
< 0.1%
71741
< 0.1%
69491
< 0.1%

BUN
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct284
Distinct (%)1.4%
Missing427
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean22.49028078
Minimum1
Maximum232
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:00.826243image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q112
median17
Q326
95-th percentile59.5
Maximum232
Range231
Interquartile range (IQR)14

Descriptive statistics

Standard deviation18.27856067
Coefficient of variation (CV)0.812731546
Kurtosis10.28869399
Mean22.49028078
Median Absolute Deviation (MAD)6
Skewness2.698542597
Sum447759
Variance334.1057801
MonotonicityNot monotonic
2021-11-29T11:22:00.920246image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13838
 
4.1%
14832
 
4.1%
11830
 
4.1%
12806
 
4.0%
15786
 
3.9%
16740
 
3.6%
10719
 
3.5%
17647
 
3.2%
9609
 
3.0%
18597
 
2.9%
Other values (274)12505
61.5%
ValueCountFrequency (%)
11
 
< 0.1%
1.51
 
< 0.1%
214
 
0.1%
2.55
 
< 0.1%
349
 
0.2%
3.520
 
0.1%
489
0.4%
4.535
 
0.2%
5190
0.9%
5.567
 
0.3%
ValueCountFrequency (%)
2321
< 0.1%
187.51
< 0.1%
1771
< 0.1%
175.51
< 0.1%
1721
< 0.1%
169.51
< 0.1%
1691
< 0.1%
166.51
< 0.1%
1661
< 0.1%
1641
< 0.1%

Alkalinephos
Real number (ℝ≥0)

MISSING

Distinct679
Distinct (%)11.9%
Missing14633
Missing (%)72.0%
Infinite0
Infinite (%)0.0%
Mean109.3258811
Minimum7
Maximum3726
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:01.016202image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile37
Q156.5
median77
Q3114
95-th percentile277.9
Maximum3726
Range3719
Interquartile range (IQR)57.5

Descriptive statistics

Standard deviation131.6314989
Coefficient of variation (CV)1.204028703
Kurtosis170.2751897
Mean109.3258811
Median Absolute Deviation (MAD)25
Skewness9.686414502
Sum623485.5
Variance17326.8515
MonotonicityNot monotonic
2021-11-29T11:22:01.113291image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5978
 
0.4%
6774
 
0.4%
5574
 
0.4%
6371
 
0.3%
6070
 
0.3%
4969
 
0.3%
6168
 
0.3%
5368
 
0.3%
5266
 
0.3%
6965
 
0.3%
Other values (669)5000
 
24.6%
(Missing)14633
72.0%
ValueCountFrequency (%)
71
 
< 0.1%
121
 
< 0.1%
151
 
< 0.1%
171
 
< 0.1%
181
 
< 0.1%
191
 
< 0.1%
19.52
< 0.1%
202
< 0.1%
223
< 0.1%
22.51
 
< 0.1%
ValueCountFrequency (%)
37261
< 0.1%
25281
< 0.1%
23321
< 0.1%
2145.51
< 0.1%
20201
< 0.1%
16691
< 0.1%
15001
< 0.1%
14511
< 0.1%
14371
< 0.1%
12791
< 0.1%

Calcium
Real number (ℝ≥0)

MISSING

Distinct187
Distinct (%)1.1%
Missing3789
Missing (%)18.6%
Infinite0
Infinite (%)0.0%
Mean8.347399831
Minimum3.9
Maximum17.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:01.216529image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum3.9
5-th percentile7.3
Q17.9
median8.3
Q38.75
95-th percentile9.4
Maximum17.5
Range13.6
Interquartile range (IQR)0.85

Descriptive statistics

Standard deviation0.6970001317
Coefficient of variation (CV)0.08349907107
Kurtosis7.022790756
Mean8.347399831
Median Absolute Deviation (MAD)0.4
Skewness0.7303607778
Sum138124.425
Variance0.4858091837
MonotonicityNot monotonic
2021-11-29T11:22:01.322896image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.3855
 
4.2%
8.2824
 
4.1%
8.5822
 
4.0%
8.4810
 
4.0%
8.1763
 
3.8%
8.6735
 
3.6%
8702
 
3.5%
8.7702
 
3.5%
8.8630
 
3.1%
7.9621
 
3.1%
Other values (177)9083
44.7%
(Missing)3789
18.6%
ValueCountFrequency (%)
3.91
 
< 0.1%
4.52
< 0.1%
4.72
< 0.1%
5.21
 
< 0.1%
5.33
< 0.1%
5.41
 
< 0.1%
5.51
 
< 0.1%
5.63
< 0.1%
5.71
 
< 0.1%
5.71
 
< 0.1%
ValueCountFrequency (%)
17.51
< 0.1%
15.71
< 0.1%
15.61
< 0.1%
15.41
< 0.1%
14.951
< 0.1%
14.51
< 0.1%
14.151
< 0.1%
13.951
< 0.1%
13.11
< 0.1%
131
< 0.1%

Chloride
Real number (ℝ≥0)

MISSING

Distinct115
Distinct (%)0.6%
Missing542
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean105.5525538
Minimum67.5
Maximum139
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:01.425773image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum67.5
5-th percentile97
Q1102.5
median106
Q3109
95-th percentile113.5
Maximum139
Range71.5
Interquartile range (IQR)6.5

Descriptive statistics

Standard deviation5.188519711
Coefficient of variation (CV)0.04915579514
Kurtosis1.865026289
Mean105.5525538
Median Absolute Deviation (MAD)3
Skewness-0.2435998154
Sum2089307.25
Variance26.9207368
MonotonicityNot monotonic
2021-11-29T11:22:01.523109image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1061410
 
6.9%
1071373
 
6.8%
1051328
 
6.5%
1081212
 
6.0%
1041158
 
5.7%
1091080
 
5.3%
1031030
 
5.1%
110856
 
4.2%
102830
 
4.1%
101703
 
3.5%
Other values (105)8814
43.3%
ValueCountFrequency (%)
67.51
 
< 0.1%
701
 
< 0.1%
731
 
< 0.1%
741
 
< 0.1%
792
< 0.1%
801
 
< 0.1%
814
< 0.1%
822
< 0.1%
82.51
 
< 0.1%
834
< 0.1%
ValueCountFrequency (%)
1391
 
< 0.1%
1361
 
< 0.1%
1341
 
< 0.1%
1331
 
< 0.1%
132.51
 
< 0.1%
1313
< 0.1%
130.51
 
< 0.1%
1292
 
< 0.1%
128.51
 
< 0.1%
1286
< 0.1%

Creatinine
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct309
Distinct (%)1.6%
Missing461
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean1.296369811
Minimum0.1
Maximum28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:01.699681image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.5
Q10.7
median0.9
Q31.2
95-th percentile3.9
Maximum28
Range27.9
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation1.412576324
Coefficient of variation (CV)1.089639941
Kurtosis28.50670414
Mean1.296369811
Median Absolute Deviation (MAD)0.25
Skewness4.437319699
Sum25765.35
Variance1.995371872
MonotonicityNot monotonic
2021-11-29T11:22:01.790321image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.72048
 
10.1%
0.81998
 
9.8%
0.91698
 
8.3%
0.61638
 
8.1%
11233
 
6.1%
0.51080
 
5.3%
1.1882
 
4.3%
0.75603
 
3.0%
1.2569
 
2.8%
0.85494
 
2.4%
Other values (299)7632
37.5%
ValueCountFrequency (%)
0.17
 
< 0.1%
0.153
 
< 0.1%
0.221
 
0.1%
0.2511
 
0.1%
0.398
 
0.5%
0.34
 
< 0.1%
0.3559
 
0.3%
0.4401
2.0%
0.454
 
< 0.1%
0.45157
 
0.8%
ValueCountFrequency (%)
281
< 0.1%
18.21
< 0.1%
17.61
< 0.1%
17.31
< 0.1%
15.851
< 0.1%
15.81
< 0.1%
15.71
< 0.1%
15.61
< 0.1%
14.751
< 0.1%
14.651
< 0.1%

Bilirubin_direct
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct147
Distinct (%)25.1%
Missing19750
Missing (%)97.1%
Infinite0
Infinite (%)0.0%
Mean2.631399317
Minimum0.1
Maximum37.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:01.889863image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.1
Q10.4
median1
Q32.9
95-th percentile9.8875
Maximum37.5
Range37.4
Interquartile range (IQR)2.5

Descriptive statistics

Standard deviation4.444859175
Coefficient of variation (CV)1.689161787
Kurtosis18.54377071
Mean2.631399317
Median Absolute Deviation (MAD)0.8
Skewness3.80559874
Sum1542
Variance19.75677308
MonotonicityNot monotonic
2021-11-29T11:22:01.985122image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.253
 
0.3%
0.143
 
0.2%
0.442
 
0.2%
0.331
 
0.2%
0.627
 
0.1%
0.524
 
0.1%
0.820
 
0.1%
0.715
 
0.1%
0.914
 
0.1%
1.613
 
0.1%
Other values (137)304
 
1.5%
(Missing)19750
97.1%
ValueCountFrequency (%)
0.143
0.2%
0.253
0.3%
0.252
 
< 0.1%
0.331
0.2%
0.355
 
< 0.1%
0.442
0.2%
0.453
 
< 0.1%
0.524
0.1%
0.553
 
< 0.1%
0.627
0.1%
ValueCountFrequency (%)
37.51
< 0.1%
351
< 0.1%
301
< 0.1%
25.951
< 0.1%
25.21
< 0.1%
22.21
< 0.1%
21.651
< 0.1%
21.21
< 0.1%
211
< 0.1%
19.81
< 0.1%

Glucose
Real number (ℝ≥0)

MISSING

Distinct702
Distinct (%)3.5%
Missing407
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean130.3958929
Minimum19
Maximum755
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:02.085694image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum19
5-th percentile87
Q1107.5
median123
Q3143.5
95-th percentile199
Maximum755
Range736
Interquartile range (IQR)36

Descriptive statistics

Standard deviation38.94551034
Coefficient of variation (CV)0.2986712961
Kurtosis17.93101417
Mean130.3958929
Median Absolute Deviation (MAD)17.5
Skewness2.760072682
Sum2598659.75
Variance1516.752776
MonotonicityNot monotonic
2021-11-29T11:22:02.181539image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
119276
 
1.4%
118270
 
1.3%
121265
 
1.3%
109261
 
1.3%
112249
 
1.2%
114245
 
1.2%
116241
 
1.2%
127236
 
1.2%
120235
 
1.2%
123234
 
1.2%
Other values (692)17417
85.6%
(Missing)407
 
2.0%
ValueCountFrequency (%)
191
< 0.1%
311
< 0.1%
382
< 0.1%
401
< 0.1%
411
< 0.1%
422
< 0.1%
462
< 0.1%
472
< 0.1%
481
< 0.1%
491
< 0.1%
ValueCountFrequency (%)
7551
< 0.1%
671.51
< 0.1%
6661
< 0.1%
5631
< 0.1%
5421
< 0.1%
5311
< 0.1%
522.51
< 0.1%
5011
< 0.1%
482.51
< 0.1%
4721
< 0.1%

Lactate
Real number (ℝ≥0)

MISSING

Distinct346
Distinct (%)4.5%
Missing12603
Missing (%)62.0%
Infinite0
Infinite (%)0.0%
Mean2.049350834
Minimum0.3
Maximum26.95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:02.283565image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.3
5-th percentile0.8
Q11.2
median1.6
Q32.3
95-th percentile4.5
Maximum26.95
Range26.65
Interquartile range (IQR)1.1

Descriptive statistics

Standard deviation1.693545629
Coefficient of variation (CV)0.8263815063
Kurtosis37.86768288
Mean2.049350834
Median Absolute Deviation (MAD)0.5
Skewness4.906191223
Sum15847.63
Variance2.868096798
MonotonicityNot monotonic
2021-11-29T11:22:02.381176image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1395
 
1.9%
1.2385
 
1.9%
1.4371
 
1.8%
1.3366
 
1.8%
1.1357
 
1.8%
0.9327
 
1.6%
1.5321
 
1.6%
1.6312
 
1.5%
1.7268
 
1.3%
1.8259
 
1.3%
Other values (336)4372
 
21.5%
(Missing)12603
62.0%
ValueCountFrequency (%)
0.33
 
< 0.1%
0.371
 
< 0.1%
0.44
 
< 0.1%
0.520
 
0.1%
0.558
 
< 0.1%
0.665
0.3%
0.63
 
< 0.1%
0.6511
 
0.1%
0.655
 
< 0.1%
0.7131
0.6%
ValueCountFrequency (%)
26.951
< 0.1%
24.851
< 0.1%
22.31
< 0.1%
19.91
< 0.1%
19.31
< 0.1%
192
< 0.1%
18.21
< 0.1%
17.81
< 0.1%
17.51
< 0.1%
17.1251
< 0.1%

Magnesium
Real number (ℝ≥0)

MISSING

Distinct101
Distinct (%)0.5%
Missing1388
Missing (%)6.8%
Infinite0
Infinite (%)0.0%
Mean2.014033407
Minimum0.8
Maximum8.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:02.478111image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.8
5-th percentile1.6
Q11.8
median2
Q32.2
95-th percentile2.55
Maximum8.2
Range7.4
Interquartile range (IQR)0.4

Descriptive statistics

Standard deviation0.3214007491
Coefficient of variation (CV)0.1595806445
Kurtosis18.47951537
Mean2.014033407
Median Absolute Deviation (MAD)0.2
Skewness1.820237523
Sum38161.905
Variance0.1032984415
MonotonicityNot monotonic
2021-11-29T11:22:02.574475image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22332
11.5%
1.92190
 
10.8%
2.11800
 
8.9%
1.81626
 
8.0%
2.21414
 
7.0%
1.71114
 
5.5%
2.3975
 
4.8%
1.6764
 
3.8%
1.85606
 
3.0%
2.4588
 
2.9%
Other values (91)5539
27.2%
(Missing)1388
 
6.8%
ValueCountFrequency (%)
0.82
 
< 0.1%
0.92
 
< 0.1%
110
 
< 0.1%
1.051
 
< 0.1%
1.114
 
0.1%
1.151
 
< 0.1%
1.236
0.2%
1.22
 
< 0.1%
1.259
 
< 0.1%
1.32
 
< 0.1%
ValueCountFrequency (%)
8.21
< 0.1%
6.91
< 0.1%
6.61
< 0.1%
6.51
< 0.1%
6.21
< 0.1%
4.71
< 0.1%
4.51
< 0.1%
4.41
< 0.1%
4.22
< 0.1%
4.12
< 0.1%

Phosphate
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct277
Distinct (%)1.7%
Missing3650
Missing (%)17.9%
Infinite0
Infinite (%)0.0%
Mean3.549626933
Minimum0.45
Maximum14.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:02.675648image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.45
5-th percentile2
Q12.8
median3.35
Q34.05
95-th percentile5.7
Maximum14.7
Range14.25
Interquartile range (IQR)1.25

Descriptive statistics

Standard deviation1.208313267
Coefficient of variation (CV)0.3404057073
Kurtosis6.749329766
Mean3.549626933
Median Absolute Deviation (MAD)0.65
Skewness1.772552306
Sum59229.075
Variance1.46002095
MonotonicityNot monotonic
2021-11-29T11:22:02.770818image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.2597
 
2.9%
3586
 
2.9%
3.3577
 
2.8%
3.5559
 
2.7%
3.1546
 
2.7%
2.8531
 
2.6%
3.4520
 
2.6%
3.7487
 
2.4%
2.9481
 
2.4%
2.7473
 
2.3%
Other values (267)11329
55.7%
(Missing)3650
 
17.9%
ValueCountFrequency (%)
0.451
 
< 0.1%
0.52
 
< 0.1%
0.61
 
< 0.1%
0.71
 
< 0.1%
0.82
 
< 0.1%
0.852
 
< 0.1%
0.97
< 0.1%
0.951
 
< 0.1%
17
< 0.1%
1.052
 
< 0.1%
ValueCountFrequency (%)
14.71
< 0.1%
14.351
< 0.1%
13.651
< 0.1%
13.31
< 0.1%
13.051
< 0.1%
131
< 0.1%
12.91
< 0.1%
12.651
< 0.1%
12.61
< 0.1%
12.51
< 0.1%

Potassium
Real number (ℝ≥0)

MISSING

Distinct144
Distinct (%)0.7%
Missing433
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean4.123865749
Minimum2.2
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:02.870415image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum2.2
5-th percentile3.4
Q13.8
median4.1
Q34.4
95-th percentile5
Maximum9
Range6.8
Interquartile range (IQR)0.6

Descriptive statistics

Standard deviation0.486336847
Coefficient of variation (CV)0.1179322695
Kurtosis2.429622932
Mean4.123865749
Median Absolute Deviation (MAD)0.3
Skewness0.8499025233
Sum82077.3
Variance0.2365235288
MonotonicityNot monotonic
2021-11-29T11:22:02.968044image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41552
 
7.6%
4.11396
 
6.9%
3.91342
 
6.6%
3.81276
 
6.3%
4.21237
 
6.1%
4.31074
 
5.3%
3.71005
 
4.9%
4.4943
 
4.6%
4.5754
 
3.7%
3.6686
 
3.4%
Other values (134)8638
42.5%
ValueCountFrequency (%)
2.21
 
< 0.1%
2.52
 
< 0.1%
2.62
 
< 0.1%
2.651
 
< 0.1%
2.75
 
< 0.1%
2.752
 
< 0.1%
2.815
0.1%
2.852
 
< 0.1%
2.913
0.1%
2.93
 
< 0.1%
ValueCountFrequency (%)
91
 
< 0.1%
7.31
 
< 0.1%
7.12
< 0.1%
6.93
< 0.1%
6.82
< 0.1%
6.82
< 0.1%
6.72
< 0.1%
6.63
< 0.1%
6.552
< 0.1%
6.53
< 0.1%

Bilirubin_total
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct360
Distinct (%)6.2%
Missing14566
Missing (%)71.6%
Infinite0
Infinite (%)0.0%
Mean1.752551993
Minimum0.1
Maximum45.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:03.144394image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.2
Q10.4
median0.7
Q31.35
95-th percentile6.5
Maximum45.9
Range45.8
Interquartile range (IQR)0.95

Descriptive statistics

Standard deviation3.848280915
Coefficient of variation (CV)2.195815548
Kurtosis44.52482792
Mean1.752551993
Median Absolute Deviation (MAD)0.35
Skewness5.996750738
Sum10112.225
Variance14.809266
MonotonicityNot monotonic
2021-11-29T11:22:03.243150image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.3522
 
2.6%
0.4520
 
2.6%
0.5509
 
2.5%
0.6420
 
2.1%
0.7381
 
1.9%
0.2322
 
1.6%
0.8307
 
1.5%
0.9239
 
1.2%
1189
 
0.9%
1.1142
 
0.7%
Other values (350)2219
 
10.9%
(Missing)14566
71.6%
ValueCountFrequency (%)
0.165
 
0.3%
0.1511
 
0.1%
0.2322
1.6%
0.2543
 
0.2%
0.3522
2.6%
0.38
 
< 0.1%
0.3547
 
0.2%
0.4520
2.6%
0.457
 
< 0.1%
0.4558
 
0.3%
ValueCountFrequency (%)
45.91
< 0.1%
45.751
< 0.1%
44.91
< 0.1%
44.11
< 0.1%
43.21
< 0.1%
42.351
< 0.1%
40.751
< 0.1%
40.151
< 0.1%
39.61
< 0.1%
391
< 0.1%

TroponinI
Real number (ℝ≥0)

MISSING

Distinct254
Distinct (%)51.9%
Missing19847
Missing (%)97.6%
Infinite0
Infinite (%)0.0%
Mean8.897239264
Minimum0.3
Maximum48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:03.342062image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.3
5-th percentile0.35
Q10.8
median3.4
Q312.7
95-th percentile36.54
Maximum48
Range47.7
Interquartile range (IQR)11.9

Descriptive statistics

Standard deviation11.46288056
Coefficient of variation (CV)1.288363752
Kurtosis1.758906915
Mean8.897239264
Median Absolute Deviation (MAD)2.95
Skewness1.606216678
Sum4350.75
Variance131.3976307
MonotonicityNot monotonic
2021-11-29T11:22:03.443628image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.525
 
0.1%
0.423
 
0.1%
0.323
 
0.1%
0.821
 
0.1%
0.613
 
0.1%
0.712
 
0.1%
18
 
< 0.1%
1.27
 
< 0.1%
0.97
 
< 0.1%
1.156
 
< 0.1%
Other values (244)344
 
1.7%
(Missing)19847
97.6%
ValueCountFrequency (%)
0.323
0.1%
0.353
 
< 0.1%
0.423
0.1%
0.451
 
< 0.1%
0.453
 
< 0.1%
0.525
0.1%
0.552
 
< 0.1%
0.613
0.1%
0.651
 
< 0.1%
0.712
0.1%
ValueCountFrequency (%)
481
< 0.1%
47.51
< 0.1%
46.51
< 0.1%
461
< 0.1%
452
< 0.1%
44.81
< 0.1%
44.21
< 0.1%
42.91
< 0.1%
42.51
< 0.1%
42.21
< 0.1%

Hct
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct841
Distinct (%)4.2%
Missing364
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean31.65418962
Minimum10.15
Maximum66.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:03.542323image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum10.15
5-th percentile25.1
Q128.35
median31
Q334.5
95-th percentile40.1
Maximum66.4
Range56.25
Interquartile range (IQR)6.15

Descriptive statistics

Standard deviation4.638895848
Coefficient of variation (CV)0.14654919
Kurtosis0.9451377878
Mean31.65418962
Median Absolute Deviation (MAD)3
Skewness0.6595302332
Sum632197.475
Variance21.51935469
MonotonicityNot monotonic
2021-11-29T11:22:03.632809image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
29218
 
1.1%
31194
 
1.0%
30191
 
0.9%
32180
 
0.9%
30.5164
 
0.8%
28164
 
0.8%
31.1158
 
0.8%
27155
 
0.8%
28.1154
 
0.8%
31.5150
 
0.7%
Other values (831)18244
89.7%
(Missing)364
 
1.8%
ValueCountFrequency (%)
10.151
< 0.1%
121
< 0.1%
14.41
< 0.1%
14.551
< 0.1%
16.81
< 0.1%
16.91
< 0.1%
17.751
< 0.1%
18.251
< 0.1%
18.31
< 0.1%
18.41
< 0.1%
ValueCountFrequency (%)
66.41
< 0.1%
62.451
< 0.1%
61.71
< 0.1%
61.051
< 0.1%
58.21
< 0.1%
56.11
< 0.1%
55.851
< 0.1%
55.32
< 0.1%
54.751
< 0.1%
54.51
< 0.1%

Hgb
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct393
Distinct (%)2.0%
Missing507
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean10.76507539
Minimum3.3
Maximum20.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:03.731647image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum3.3
5-th percentile8.4
Q19.6
median10.6
Q311.75
95-th percentile13.8
Maximum20.3
Range17
Interquartile range (IQR)2.15

Descriptive statistics

Standard deviation1.649797292
Coefficient of variation (CV)0.1532545971
Kurtosis0.4726858849
Mean10.76507539
Median Absolute Deviation (MAD)1.05
Skewness0.5523234009
Sum213460.68
Variance2.721831106
MonotonicityNot monotonic
2021-11-29T11:22:03.831285image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.5418
 
2.1%
10412
 
2.0%
10.2401
 
2.0%
10.3399
 
2.0%
9.8388
 
1.9%
9.7380
 
1.9%
10.8372
 
1.8%
10.1365
 
1.8%
10.7360
 
1.8%
10.6354
 
1.7%
Other values (383)15980
78.6%
(Missing)507
 
2.5%
ValueCountFrequency (%)
3.31
< 0.1%
4.151
< 0.1%
5.42
< 0.1%
5.61
< 0.1%
5.81
< 0.1%
61
< 0.1%
6.0251
< 0.1%
6.051
< 0.1%
6.12
< 0.1%
6.1751
< 0.1%
ValueCountFrequency (%)
20.31
< 0.1%
19.81
< 0.1%
19.32
< 0.1%
18.62
< 0.1%
18.451
< 0.1%
18.051
< 0.1%
17.951
< 0.1%
17.71
< 0.1%
17.62
< 0.1%
17.451
< 0.1%

PTT
Real number (ℝ≥0)

MISSING

Distinct1709
Distinct (%)10.8%
Missing4496
Missing (%)22.1%
Infinite0
Infinite (%)0.0%
Mean35.82851452
Minimum16.9
Maximum150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:03.935591image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum16.9
5-th percentile23.1
Q127
median30.9
Q337.6
95-th percentile68.2
Maximum150
Range133.1
Interquartile range (IQR)10.6

Descriptive statistics

Standard deviation16.43467255
Coefficient of variation (CV)0.4587037104
Kurtosis13.90541029
Mean35.82851452
Median Absolute Deviation (MAD)4.7
Skewness3.226363629
Sum567523.67
Variance270.0984618
MonotonicityNot monotonic
2021-11-29T11:22:04.038103image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27.7100
 
0.5%
27.6100
 
0.5%
26.597
 
0.5%
28.196
 
0.5%
28.696
 
0.5%
2895
 
0.5%
29.393
 
0.5%
29.592
 
0.5%
28.991
 
0.4%
26.491
 
0.4%
Other values (1699)14889
73.2%
(Missing)4496
 
22.1%
ValueCountFrequency (%)
16.91
< 0.1%
17.11
< 0.1%
17.21
< 0.1%
17.31
< 0.1%
17.651
< 0.1%
18.11
< 0.1%
18.251
< 0.1%
18.42
< 0.1%
18.451
< 0.1%
18.52
< 0.1%
ValueCountFrequency (%)
15052
0.3%
148.41
 
< 0.1%
147.61
 
< 0.1%
1472
 
< 0.1%
145.91
 
< 0.1%
145.51
 
< 0.1%
144.21
 
< 0.1%
144.11
 
< 0.1%
143.71
 
< 0.1%
142.11
 
< 0.1%

WBC
Real number (ℝ≥0)

MISSING

Distinct984
Distinct (%)5.0%
Missing625
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean11.69814266
Minimum0.1
Maximum319.25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:04.140035image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile5
Q18.2
median10.8
Q313.95
95-th percentile20.6
Maximum319.25
Range319.15
Interquartile range (IQR)5.75

Descriptive statistics

Standard deviation6.675437823
Coefficient of variation (CV)0.5706408287
Kurtosis334.9965445
Mean11.69814266
Median Absolute Deviation (MAD)2.85
Skewness10.89622191
Sum230582.09
Variance44.56147013
MonotonicityNot monotonic
2021-11-29T11:22:04.234166image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.3181
 
0.9%
9.8161
 
0.8%
10.2159
 
0.8%
9159
 
0.8%
10157
 
0.8%
11.2155
 
0.8%
10.7154
 
0.8%
9.2151
 
0.7%
8.5149
 
0.7%
9.7147
 
0.7%
Other values (974)18138
89.2%
(Missing)625
 
3.1%
ValueCountFrequency (%)
0.17
< 0.1%
0.151
 
< 0.1%
0.211
0.1%
0.251
 
< 0.1%
0.32
 
< 0.1%
0.44
 
< 0.1%
0.452
 
< 0.1%
0.52
 
< 0.1%
0.551
 
< 0.1%
0.63
 
< 0.1%
ValueCountFrequency (%)
319.251
< 0.1%
206.31
< 0.1%
168.61
< 0.1%
160.61
< 0.1%
150.41
< 0.1%
135.41
< 0.1%
126.21
< 0.1%
120.51
< 0.1%
119.91
< 0.1%
116.51
< 0.1%

Fibrinogen
Real number (ℝ≥0)

MISSING

Distinct819
Distinct (%)31.9%
Missing17769
Missing (%)87.4%
Infinite0
Infinite (%)0.0%
Mean311.0294897
Minimum52.5
Maximum1383
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:04.332661image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum52.5
5-th percentile124
Q1193
median263
Q3384
95-th percentile655.35
Maximum1383
Range1330.5
Interquartile range (IQR)191

Descriptive statistics

Standard deviation168.1038227
Coefficient of variation (CV)0.5404755121
Kurtosis2.677224558
Mean311.0294897
Median Absolute Deviation (MAD)85
Skewness1.45608704
Sum798412.7
Variance28258.89521
MonotonicityNot monotonic
2021-11-29T11:22:04.437062image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20216
 
0.1%
21415
 
0.1%
21714
 
0.1%
22214
 
0.1%
23914
 
0.1%
18314
 
0.1%
16813
 
0.1%
20613
 
0.1%
23313
 
0.1%
24813
 
0.1%
Other values (809)2428
 
11.9%
(Missing)17769
87.4%
ValueCountFrequency (%)
52.51
 
< 0.1%
581
 
< 0.1%
61.51
 
< 0.1%
631
 
< 0.1%
651
 
< 0.1%
763
< 0.1%
781
 
< 0.1%
791
 
< 0.1%
801
 
< 0.1%
80.51
 
< 0.1%
ValueCountFrequency (%)
13831
< 0.1%
12461
< 0.1%
12111
< 0.1%
11611
< 0.1%
10511
< 0.1%
10301
< 0.1%
9761
< 0.1%
9601
< 0.1%
9561
< 0.1%
9461
< 0.1%

Platelets
Real number (ℝ≥0)

MISSING

Distinct1229
Distinct (%)6.2%
Missing585
Missing (%)2.9%
Infinite0
Infinite (%)0.0%
Mean211.4816819
Minimum7
Maximum1687.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:04.615737image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile84
Q1143.5
median193
Q3256
95-th percentile400
Maximum1687.5
Range1680.5
Interquartile range (IQR)112.5

Descriptive statistics

Standard deviation105.563872
Coefficient of variation (CV)0.4991631947
Kurtosis10.53365289
Mean211.4816819
Median Absolute Deviation (MAD)55
Skewness2.062033431
Sum4176974.7
Variance11143.73107
MonotonicityNot monotonic
2021-11-29T11:22:04.712639image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18097
 
0.5%
19590
 
0.4%
19388
 
0.4%
17987
 
0.4%
18487
 
0.4%
18586
 
0.4%
16386
 
0.4%
18684
 
0.4%
16784
 
0.4%
20182
 
0.4%
Other values (1219)18880
92.8%
(Missing)585
 
2.9%
ValueCountFrequency (%)
71
 
< 0.1%
8.51
 
< 0.1%
93
< 0.1%
9.51
 
< 0.1%
101
 
< 0.1%
11.51
 
< 0.1%
131
 
< 0.1%
141
 
< 0.1%
14.52
< 0.1%
151
 
< 0.1%
ValueCountFrequency (%)
1687.51
< 0.1%
15441
< 0.1%
13431
< 0.1%
1300.51
< 0.1%
11911
< 0.1%
1167.51
< 0.1%
1125.51
< 0.1%
1096.51
< 0.1%
1067.51
< 0.1%
1056.51
< 0.1%

Age
Real number (ℝ≥0)

Distinct5971
Distinct (%)29.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.6216129
Minimum18.11
Maximum89
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:04.816806image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum18.11
5-th percentile30.8475
Q152.29
median64.67
Q375.66
95-th percentile84.95
Maximum89
Range70.89
Interquartile range (IQR)23.37

Descriptive statistics

Standard deviation16.23615352
Coefficient of variation (CV)0.2592739594
Kurtosis-0.2520549698
Mean62.6216129
Median Absolute Deviation (MAD)11.61
Skewness-0.5902903968
Sum1273473.12
Variance263.6126812
MonotonicityNot monotonic
2021-11-29T11:22:04.915794image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
65.8213
 
0.1%
69.6812
 
0.1%
61.0812
 
0.1%
68.1712
 
0.1%
65.4712
 
0.1%
71.3712
 
0.1%
68.3711
 
0.1%
69.5811
 
0.1%
78.4211
 
0.1%
60.8811
 
0.1%
Other values (5961)20219
99.4%
ValueCountFrequency (%)
18.113
< 0.1%
18.131
 
< 0.1%
18.142
< 0.1%
18.151
 
< 0.1%
18.181
 
< 0.1%
18.241
 
< 0.1%
18.321
 
< 0.1%
18.341
 
< 0.1%
18.352
< 0.1%
18.361
 
< 0.1%
ValueCountFrequency (%)
891
 
< 0.1%
88.991
 
< 0.1%
88.982
 
< 0.1%
88.974
< 0.1%
88.961
 
< 0.1%
88.954
< 0.1%
88.942
 
< 0.1%
88.931
 
< 0.1%
88.925
< 0.1%
88.94
< 0.1%

Gender
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size159.0 KiB
1.0
11834 
0.0
8502 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters61008
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.011834
58.2%
0.08502
41.8%

Length

2021-11-29T11:22:05.013946image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:22:05.067390image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
1.011834
58.2%
0.08502
41.8%

Most occurring characters

ValueCountFrequency (%)
028838
47.3%
.20336
33.3%
111834
19.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number40672
66.7%
Other Punctuation20336
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
028838
70.9%
111834
29.1%
Other Punctuation
ValueCountFrequency (%)
.20336
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common61008
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
028838
47.3%
.20336
33.3%
111834
19.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII61008
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
028838
47.3%
.20336
33.3%
111834
19.4%

Unit1
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct2
Distinct (%)< 0.1%
Missing9522
Missing (%)46.8%
Memory size159.0 KiB
0.0
5470 
1.0
5344 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters32442
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row1.0
3rd row0.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
0.05470
26.9%
1.05344
26.3%
(Missing)9522
46.8%

Length

2021-11-29T11:22:05.119803image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:22:05.168986image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
0.05470
50.6%
1.05344
49.4%

Most occurring characters

ValueCountFrequency (%)
016284
50.2%
.10814
33.3%
15344
 
16.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number21628
66.7%
Other Punctuation10814
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
016284
75.3%
15344
 
24.7%
Other Punctuation
ValueCountFrequency (%)
.10814
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common32442
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
016284
50.2%
.10814
33.3%
15344
 
16.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII32442
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
016284
50.2%
.10814
33.3%
15344
 
16.5%

Unit2
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct2
Distinct (%)< 0.1%
Missing9522
Missing (%)46.8%
Memory size159.0 KiB
1.0
5470 
0.0
5344 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters32442
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row0.0
3rd row1.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
1.05470
26.9%
0.05344
26.3%
(Missing)9522
46.8%

Length

2021-11-29T11:22:05.221086image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:22:05.270237image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
1.05470
50.6%
0.05344
49.4%

Most occurring characters

ValueCountFrequency (%)
016158
49.8%
.10814
33.3%
15470
 
16.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number21628
66.7%
Other Punctuation10814
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
016158
74.7%
15470
 
25.3%
Other Punctuation
ValueCountFrequency (%)
.10814
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common32442
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
016158
49.8%
.10814
33.3%
15470
 
16.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII32442
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
016158
49.8%
.10814
33.3%
15470
 
16.9%

HospAdmTime
Real number (ℝ)

Distinct7152
Distinct (%)35.2%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean-48.67841062
Minimum-3710.66
Maximum23.99
Zeros168
Zeros (%)0.8%
Negative19912
Negative (%)97.9%
Memory size159.0 KiB
2021-11-29T11:22:05.333161image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-3710.66
5-th percentile-236.12
Q1-34.135
median-2.77
Q3-0.02
95-th percentile-0.01
Maximum23.99
Range3734.65
Interquartile range (IQR)34.115

Descriptive statistics

Standard deviation143.6833182
Coefficient of variation (CV)-2.951684666
Kurtosis123.0885825
Mean-48.67841062
Median Absolute Deviation (MAD)2.75
Skewness-8.542504055
Sum-989875.48
Variance20644.89593
MonotonicityNot monotonic
2021-11-29T11:22:05.433252image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.023749
 
18.4%
-0.032290
 
11.3%
-0.011114
 
5.5%
-0.04658
 
3.2%
-0.05314
 
1.5%
0168
 
0.8%
-0.06136
 
0.7%
-0.0782
 
0.4%
-0.0840
 
0.2%
-0.0932
 
0.2%
Other values (7142)11752
57.8%
ValueCountFrequency (%)
-3710.661
< 0.1%
-3322.91
< 0.1%
-3269.11
< 0.1%
-3212.561
< 0.1%
-3141.551
< 0.1%
-2668.771
< 0.1%
-2562.531
< 0.1%
-2506.691
< 0.1%
-2476.581
< 0.1%
-2379.761
< 0.1%
ValueCountFrequency (%)
23.991
< 0.1%
22.041
< 0.1%
20.041
< 0.1%
17.341
< 0.1%
16.021
< 0.1%
14.651
< 0.1%
14.211
< 0.1%
141
< 0.1%
11.941
< 0.1%
10.991
< 0.1%

ICULOS
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct226
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.84522522
Minimum4.5
Maximum320
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:05.541139image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum4.5
5-th percentile8.5
Q114
median20.5
Q325
95-th percentile30
Maximum320
Range315.5
Interquartile range (IQR)11

Descriptive statistics

Standard deviation11.71782428
Coefficient of variation (CV)0.5621346929
Kurtosis84.39630215
Mean20.84522522
Median Absolute Deviation (MAD)5.5
Skewness6.167088074
Sum423908.5
Variance137.3074058
MonotonicityNot monotonic
2021-11-29T11:22:05.638767image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21.5626
 
3.1%
22619
 
3.0%
21598
 
2.9%
23.5597
 
2.9%
20.5596
 
2.9%
20591
 
2.9%
23585
 
2.9%
22.5579
 
2.8%
24570
 
2.8%
19.5570
 
2.8%
Other values (216)14405
70.8%
ValueCountFrequency (%)
4.588
 
0.4%
587
 
0.4%
5.574
 
0.4%
687
 
0.4%
6.591
 
0.4%
7110
0.5%
7.5149
0.7%
8157
0.8%
8.5206
1.0%
9261
1.3%
ValueCountFrequency (%)
3201
 
< 0.1%
3091
 
< 0.1%
2861
 
< 0.1%
169.51
 
< 0.1%
1691
 
< 0.1%
168.55
< 0.1%
165.51
 
< 0.1%
164.51
 
< 0.1%
1541
 
< 0.1%
1531
 
< 0.1%

SepsisLabel
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size159.0 KiB
0.0
19777 
1.0
 
536
0.5
 
23

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters61008
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.019777
97.3%
1.0536
 
2.6%
0.523
 
0.1%

Length

2021-11-29T11:22:05.733405image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:22:05.788033image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
0.019777
97.3%
1.0536
 
2.6%
0.523
 
0.1%

Most occurring characters

ValueCountFrequency (%)
040113
65.8%
.20336
33.3%
1536
 
0.9%
523
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number40672
66.7%
Other Punctuation20336
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
040113
98.6%
1536
 
1.3%
523
 
0.1%
Other Punctuation
ValueCountFrequency (%)
.20336
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common61008
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
040113
65.8%
.20336
33.3%
1536
 
0.9%
523
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII61008
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
040113
65.8%
.20336
33.3%
1536
 
0.9%
523
 
< 0.1%

Sepsis
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size159.0 KiB
0.0
18546 
1.0
 
1790

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters61008
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.018546
91.2%
1.01790
 
8.8%

Length

2021-11-29T11:22:05.849078image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:22:05.902330image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
0.018546
91.2%
1.01790
 
8.8%

Most occurring characters

ValueCountFrequency (%)
038882
63.7%
.20336
33.3%
11790
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number40672
66.7%
Other Punctuation20336
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
038882
95.6%
11790
 
4.4%
Other Punctuation
ValueCountFrequency (%)
.20336
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common61008
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
038882
63.7%
.20336
33.3%
11790
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII61008
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
038882
63.7%
.20336
33.3%
11790
 
2.9%

Hours
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct228
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.85793666
Minimum8
Maximum336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.0 KiB
2021-11-29T11:22:06.039348image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile15
Q125
median39
Q347
95-th percentile58
Maximum336
Range328
Interquartile range (IQR)22

Descriptive statistics

Standard deviation22.30865867
Coefficient of variation (CV)0.5741081639
Kurtosis40.49091179
Mean38.85793666
Median Absolute Deviation (MAD)11
Skewness4.703211094
Sum790215
Variance497.6762517
MonotonicityNot monotonic
2021-11-29T11:22:06.139297image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36700
 
3.4%
39665
 
3.3%
38656
 
3.2%
40634
 
3.1%
41632
 
3.1%
37632
 
3.1%
43600
 
3.0%
42597
 
2.9%
44580
 
2.9%
46560
 
2.8%
Other values (218)14080
69.2%
ValueCountFrequency (%)
8124
 
0.6%
9122
 
0.6%
1095
 
0.5%
11114
 
0.6%
12121
 
0.6%
13145
0.7%
14194
1.0%
15231
1.1%
16274
1.3%
17348
1.7%
ValueCountFrequency (%)
3365
< 0.1%
3351
 
< 0.1%
3341
 
< 0.1%
3301
 
< 0.1%
3281
 
< 0.1%
3052
 
< 0.1%
2971
 
< 0.1%
2861
 
< 0.1%
2791
 
< 0.1%
2771
 
< 0.1%

Interactions

2021-11-29T11:21:54.695208image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:51.257627image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:51.346368image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:51.434866image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:51.526392image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:51.612162image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:51.705347image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:51.793781image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:51.954343image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:52.044188image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:52.130620image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:52.215018image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:52.300358image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:52.387262image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:52.471783image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:52.561581image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:52.647269image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:52.731560image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:52.826057image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:52.916874image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:53.009397image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:53.094824image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:53.186154image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:53.277693image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:53.364376image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:53.454611image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:53.545408image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:53.634260image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:53.718911image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:53.802670image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:53.889260image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:54.055456image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:54.144722image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:54.232227image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:54.325624image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:54.419578image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:54.510033image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:21:54.605119image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Correlations

2021-11-29T11:22:06.285066image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-11-29T11:22:06.632378image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-11-29T11:22:06.978519image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-11-29T11:22:07.268435image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2021-11-29T11:21:54.940125image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
A simple visualization of nullity by column.
2021-11-29T11:21:56.012752image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2021-11-29T11:21:56.729398image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2021-11-29T11:21:57.466604image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

PatientIDHRO2SatTempSBPMAPDBPRespEtCO2BaseExcessHCO3FiO2pHPaCO2SaO2ASTBUNAlkalinephosCalciumChlorideCreatinineBilirubin_directGlucoseLactateMagnesiumPhosphatePotassiumBilirubin_totalTroponinIHctHgbPTTWBCFibrinogenPlateletsAgeGenderUnit1Unit2HospAdmTimeICULOSSepsisLabelSepsisHours
01104.091.036.725128.0087.915NaN25.000NaN20.046.50.297.34098.088.516.018.098.09.4585.00.70NaN163.0NaN2.103.504.20.3NaN36.7012.35NaN10.2NaN327.583.140.0NaNNaN-0.0327.50.00.054.0
1260.097.036.110133.0065.00043.0012.000NaNNaN22.0NaNNaNNaNNaNNaN100.0NaN7.90113.02.50NaN78.0NaN2.504.405.1NaNNaN27.809.70NaN11.0NaN158.075.910.00.01.0-98.6012.00.00.023.0
2381.095.037.585140.0081.00053.5026.000NaN6.531.00.607.49039.5NaNNaN30.0NaN11.0099.00.90NaN113.0NaN2.402.403.8NaNNaN28.159.1030.08.7NaN486.045.820.01.00.0-1195.7124.50.00.048.0
34105.098.036.390114.5067.83550.2518.000NaN0.022.0NaN7.40043.098.0NaN16.5NaN8.20106.50.80NaN84.0NaN2.053.804.3NaNNaN25.808.3021.87.6NaN182.065.710.00.01.0-8.7715.00.00.029.0
4573.597.037.220133.5087.000NaN16.000NaNNaN25.0NaNNaNNaNNaN16.07.065.08.20105.00.60NaN128.0NaN2.202.803.60.6NaN41.0014.4029.08.0NaN276.028.091.01.00.0-0.0525.50.00.048.0
56100.598.536.670122.0089.000NaN24.000NaN0.029.00.407.34047.0NaNNaN9.0NaNNaN111.00.70NaN73.01.4NaNNaN3.8NaNNaN36.9012.20NaN12.0NaN298.052.011.01.00.0-0.0311.00.00.017.0
67121.095.037.885109.0074.50060.0021.000NaN-9.016.00.407.33027.0NaN452.066.088.07.35115.53.85NaN193.52.21.751.303.11.4NaN41.8515.3026.39.3NaN45.064.241.01.00.0-0.0523.00.00.045.0
7875.0100.036.220108.7565.00048.5016.750NaN-8.015.0NaN7.35527.0NaNNaN29.0NaN8.00106.01.20NaN108.01.61.903.504.9NaNNaN25.908.90NaN9.4NaN213.087.081.0NaNNaN-2.2320.50.00.040.0
89113.098.037.720120.0080.00065.0021.875NaN0.027.00.407.37048.097.0NaN19.0NaN8.00107.00.90NaN119.52.22.053.053.7NaNNaN27.409.6030.910.9232.5175.027.921.0NaNNaN-0.03129.50.01.0258.0
91079.096.037.000112.0072.00054.0019.000NaN0.024.00.407.40537.597.0NaN17.5NaNNaN106.01.00NaN107.01.12.10NaN3.9NaNNaN31.9010.2029.99.3NaN111.076.710.00.01.0-2.3614.00.00.023.0

Last rows

PatientIDHRO2SatTempSBPMAPDBPRespEtCO2BaseExcessHCO3FiO2pHPaCO2SaO2ASTBUNAlkalinephosCalciumChlorideCreatinineBilirubin_directGlucoseLactateMagnesiumPhosphatePotassiumBilirubin_totalTroponinIHctHgbPTTWBCFibrinogenPlateletsAgeGenderUnit1Unit2HospAdmTimeICULOSSepsisLabelSepsisHours
203262063487.5096.037.700105.2567.553.016.50NaN2.027.00.57.41543.096.0NaN15.0NaNNaN111.00.65NaN136.0NaN2.20NaN4.15NaNNaN27.559.9530.008.30NaN224.557.261.00.01.0-2.9012.50.00.020.0
203272063570.0096.036.860127.0081.062.016.00NaN0.024.0NaN7.41037.0NaNNaN12.0NaN7.80110.00.80NaN107.01.01.802.203.70NaNNaN28.7010.1039.959.00NaN301.056.751.0NaNNaN-0.0122.50.00.042.0
203282063669.5096.036.220104.0069.048.014.00NaN0.024.00.57.39041.594.01033.036.0204.0NaN104.01.35NaN82.5NaN1.90NaN4.501.8NaN27.509.5038.305.80NaN215.582.360.00.01.00.3226.00.00.043.0
203292063796.2597.036.415127.5094.074.018.00NaN-7.017.00.47.26042.0NaNNaN61.0NaN8.3095.03.80NaN164.00.71.905.605.20NaNNaN28.809.6035.8510.50NaN248.060.661.01.00.0-0.0272.50.01.0142.0
203302063880.0098.036.830145.0088.065.018.50NaNNaN30.0NaNNaNNaNNaNNaN17.0NaN9.10109.01.30NaN98.0NaN2.103.503.60NaNNaN37.7013.0024.807.60NaN176.068.381.0NaNNaN-0.0222.00.00.041.0
203312063982.0099.036.375101.2570.0NaN20.00NaNNaN19.0NaNNaNNaNNaN80.032.0154.08.20105.00.80NaN89.0NaN1.604.004.103.1NaN28.609.7033.4018.10263.025.059.141.01.00.0-0.0213.50.00.026.0
203322064079.0095.537.400125.0076.054.515.25NaN-4.020.00.77.36036.597.0NaN15.0NaN7.70106.00.70NaN153.0NaN2.10NaN4.35NaNNaN28.3011.2035.4014.30NaN148.074.530.00.01.0-59.0915.00.00.025.0
203332064184.5098.037.055113.5066.063.015.00NaNNaN30.5NaNNaNNaNNaNNaN17.0NaN8.8599.00.75NaN109.0NaN2.253.553.50NaNNaN32.6511.1023.009.15NaN302.533.011.0NaNNaN-0.0116.00.00.021.0
203342064294.00100.036.560107.0075.055.518.00NaN0.027.50.57.45034.099.0NaN12.0NaN8.85106.00.40NaN118.0NaN1.954.204.20NaNNaN30.8010.3027.407.30NaN257.069.800.0NaNNaN-10.5821.50.00.042.0
203352064390.0097.538.440149.0090.072.016.00NaN1.026.00.57.42041.098.0103.520.5128.58.30104.02.20NaN175.01.62.253.903.850.7NaN29.7011.5529.7513.95NaN325.562.291.0NaNNaN-0.0319.00.01.033.0